{"id":19120455,"url":"https://github.com/juliagaussianprocesses/approximategps.jl","last_synced_at":"2025-07-19T21:33:14.200Z","repository":{"id":40427081,"uuid":"378457747","full_name":"JuliaGaussianProcesses/ApproximateGPs.jl","owner":"JuliaGaussianProcesses","description":"Approximations for Gaussian processes: sparse variational inducing point approximations, Laplace approximation, ...","archived":false,"fork":false,"pushed_at":"2024-07-14T16:24:56.000Z","size":31993,"stargazers_count":38,"open_issues_count":25,"forks_count":7,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-06-30T10:09:24.743Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://juliagaussianprocesses.github.io/ApproximateGPs.jl/dev","language":"Julia","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/JuliaGaussianProcesses.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-06-19T16:32:31.000Z","updated_at":"2025-05-28T18:46:45.000Z","dependencies_parsed_at":"2024-07-09T02:49:31.453Z","dependency_job_id":null,"html_url":"https://github.com/JuliaGaussianProcesses/ApproximateGPs.jl","commit_stats":{"total_commits":188,"total_committers":7,"mean_commits":"26.857142857142858","dds":"0.21808510638297873","last_synced_commit":"82999e665f23fea7996de2ae9b6eeb3016d68fec"},"previous_names":[],"tags_count":23,"template":false,"template_full_name":null,"purl":"pkg:github/JuliaGaussianProcesses/ApproximateGPs.jl","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JuliaGaussianProcesses%2FApproximateGPs.jl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JuliaGaussianProcesses%2FApproximateGPs.jl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JuliaGaussianProcesses%2FApproximateGPs.jl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JuliaGaussianProcesses%2FApproximateGPs.jl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/JuliaGaussianProcesses","download_url":"https://codeload.github.com/JuliaGaussianProcesses/ApproximateGPs.jl/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JuliaGaussianProcesses%2FApproximateGPs.jl/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266019657,"owners_count":23864916,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-09T05:14:10.994Z","updated_at":"2025-07-19T21:33:14.177Z","avatar_url":"https://github.com/JuliaGaussianProcesses.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ApproximateGPs\n\n[![Docs](https://img.shields.io/badge/docs-dev-blue.svg)](https://JuliaGaussianProcesses.github.io/ApproximateGPs.jl/dev)\n[![CI](https://github.com/JuliaGaussianProcesses/ApproximateGPs.jl/actions/workflows/CI.yml/badge.svg)](https://github.com/JuliaGaussianProcesses/ApproximateGPs.jl/actions/workflows/CI.yml)\n[![Codecov](https://codecov.io/gh/JuliaGaussianProcesses/ApproximateGPs.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaGaussianProcesses/ApproximateGPs.jl)\n[![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle)\n[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)\n\n## Aim of this package\n\nProvide various algorithms for approximate inference in latent Gaussian process models, currently focussing on non-conjugate (non-Gaussian) likelihoods and sparse approximations.\n\n## Structure\n\nEach approximation lives in its own submodule (`\u003cApproximation\u003eModule`), though\nin general using the exported API is sufficient.\n\nThe main API is:\n\n* `posterior(approximation, lfx::LatentFiniteGP, ys)` to obtain the posterior\n  approximation to `lfx` conditioned on the observations `ys`.\n\n* `approx_lml(approximation, lfx::LatentFiniteGP, ys)` which returns the\n  marginal likelihood approximation that can be used for hyperparameter\n  optimisation.\n\nCurrently implemented approximations:\n\n* `LaplaceApproximation`\n\n* `SparseVariationalApproximation`\n\n  NOTE: requires optimisation of the variational distribution even for fixed\n  hyperparameters.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjuliagaussianprocesses%2Fapproximategps.jl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjuliagaussianprocesses%2Fapproximategps.jl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjuliagaussianprocesses%2Fapproximategps.jl/lists"}